Triple
T28607954
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | sifive_u board |
E724102
|
entity |
| Predicate | vendorModeledAfter |
P149676
|
FINISHED |
| Object | SiFive |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: SiFive | Statement: [sifive_u board, vendorModeledAfter, SiFive]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vendorModeledAfter Context triple: [sifive_u board, vendorModeledAfter, SiFive]
-
A.
usesProductionModel
Indicates that one entity employs or relies on another entity as its primary or official production model in practice.
-
B.
compatibilityModel
Indicates that one entity is defined or evaluated according to a specific compatibility framework, standard, or model in relation to another entity.
-
C.
modeledWith
Indicates that something is represented, simulated, or described using a particular model, method, or modeling technique.
-
D.
isModelledAfter
chosen
Indicates that one entity is created, designed, or structured based on the form, features, or principles of another entity.
-
E.
vendorType
Indicates the classification or category of a vendor based on the type of goods or services they provide.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f01d816d7c8190a1fe27e3434041dc |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f652a492108190b885b955ce147d3c |
completed | May 2, 2026, 7:38 p.m. |
| PD | Predicate disambiguation | batch_69f651aad92c8190b874b3b5f9f64434 |
completed | May 2, 2026, 7:34 p.m. |
Created at: April 28, 2026, 4:28 a.m.